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A win is a win, right?

WAR isn't the only way to calculate individual player contributions.

Goldy doing Goldy things
Goldy doing Goldy things
USA TODAY Sports

Wins Above Replacement (WAR) has slowly emerged as part of the mainstream baseball lexicon. This complicated catch-all metric is now being used on ESPN, in television broadcasts and presumably front offices across the country. Considering that the idea started in the basements and chat rooms of guys cast as outsiders, this is a pretty big victory for the advanced metric crowd, perhaps the most impressive victory that the movement has captured to date.

The statistic, however, still has more than its share of detractors. The abstract qualities of the stat still seem to stifle those who struggle to move out of the realm of immediate actuality. This abstraction is largely caused by the context neutrality of WAR, something that's critical to the stat's identity. By creating a context-neutral statistic, the inventors and refiners of WAR have (nearly) perfected a metric that can be applied across space and time. Wonder how Willie Mays stacked up in his first two seasons to Mike Trout? Wonder no more; WAR can give you an answer even though they played in different parks and different eras. For what it's worth, Mays only amassed 4.9 WAR in his first two seasons, but put up nearly 20 WAR in his next two. Trout's been off to a hotter start, but Mays had incredibly staying power, something that Trout will have to prove over time.

WAR isn't the only way to measure wins, however. WAR provides us with a projectable, context-neutral view of the wins a player contributes, but isn't necessarily the best indicator or what actually occurred on the diamond. The stat that gives us the best snapshot of what a player has provided for his team is WPA, or Win Probability Added. You're probably familiar with WPA since you're at Beyond the Box Score in the first place, but allow me to make the necessary disclaimers about WPA for those who may not be familiar.

  • WPA tells us how much a particular player contributed to his team's chances (win expectancy) of winning games
  • WPA is not considered predictive
  • WPA is a counting stat (like WAR)
  • WPA does not include fielding
  • WPA is not a way to evaluate the talent of a player
  • WAR is a way to evaluate the talent of a player
  • WPA for starting pitchers does not translate to WPA for relief pitchers, and vice versa
  • Selection bias, leverage and other factors make the two groups (SP/RP) difficult to compare
  • Others have done a far better, more thorough job of explaining just what WPA is, and I'd invite you click on the WPA links above to learn more.

In short, WAR describes context-neutral talent, WPA provides us with game-dependent outcomes. If you want to know who the best player is on your team, then WAR is your go-to. If you want to know which player has increased your team's chances of winning games so far, then consult WPA. Oftentimes, those end up being the same players. For example, the Arizona Diamondbacks marketed 2013 NL MVP candidate Paul Goldschmidt through WAR and WPA because he was a fourth in the National League by WAR and first by WPA. In general, the list of league leaders in each stat looks fairly similar by the end of the season with some reshuffling having occurred.

With that said, there are always outliers. These tend to be players with strong defensive profiles (remember, WPA doesn't calculate the glove work) or guys who aren't necessarily considered the most talented players in the game (WAR takes a heavy look at peripheral stats) but had a handful of timely performances. Brandon Moss of the Oakland A's was 10th in the AL in WPA, but 50th in WAR. How good is Brandon Moss? I'd venture to say that he's a lot closer to the 50th best American League player than the 10th in terms of talent. How much did Brandon Moss help propel the A's last year? Apparently quite a bit, so much so that only nine AL position players were more helpful to their team.

After exploring this, I decided to take a closer look at some of these outliers on the young 2014 season. First, take a look at the top 30 players in each category through Friday the 25th:

2014 WAR Leaders 2014 WPA Leaders
Name Team WAR Name Team WPA
Troy Tulowitzki Rockies 1.8 Jayson Werth Nationals 1.5
Charlie Blackmon Rockies 1.7 Giancarlo Stanton Marlins 1.5
Mike Trout Angels 1.7 Ryan Braun Brewers 1.43
Chase Utley Phillies 1.4 Michael Morse Giants 1.27
Josh Donaldson Athletics 1.3 Michael Brantley Indians 1.27
Andrew McCutchen Pirates 1.3 Jose Abreu White Sox 1.24
Brian Dozier Twins 1.3 Justin Upton Braves 1.15
Juan Uribe Dodgers 1.2 Chris Colabello Twins 1.06
Justin Upton Braves 1.1 Denard Span Nationals 1
Albert Pujols Angels 1.1 David Murphy Indians 0.97
Yadier Molina Cardinals 1.1 James Loney Rays 0.94
Evan Longoria Rays 1.1 Charlie Blackmon Rockies 0.93
Carlos Gomez Brewers 1.1 Hunter Pence Giants 0.91
Freddie Freeman Braves 1.1 Justin Morneau Rockies 0.9
Melky Cabrera Blue Jays 1.1 Chase Utley Phillies 0.88
Emilio Bonifacio Cubs 1.1 Dee Gordon Dodgers 0.87
Ben Zobrist Rays 1.1 Alberto Callaspo Athletics 0.85
Ryan Braun Brewers 1 Josmil Pinto Twins 0.83
Matt Joyce Rays 1 Alexei Ramirez White Sox 0.83
Matt Wieters Orioles 1 Mike Trout Angels 0.83
Jed Lowrie Athletics 1 Troy Tulowitzki Rockies 0.82
Giancarlo Stanton Marlins 0.9 Albert Pujols Angels 0.8
Dee Gordon Dodgers 0.9 Brandon Moss Athletics 0.79
Alexei Ramirez White Sox 0.9 Juan Uribe Dodgers 0.78
Jimmy Rollins Phillies 0.9 Jason Kipnis Indians 0.77
Joey Votto Reds 0.9 Corey Hart Mariners 0.76
Mike Napoli Red Sox 0.9 Adrian Gonzalez Dodgers 0.76
Todd Frazier Reds 0.9 Jimmy Rollins Phillies 0.72
Trevor Plouffe Twins 0.9 Josh Donaldson Athletics 0.72
Jonathan Lucroy Brewers 0.9 Joey Votto Reds 0.71

There are plenty of excellent players on each list, but there is minimal overlap. This underscores the premise described above: talent vs. outcomes. To further draw out the point, let's take a look at the top 30 "context winners", guys who have outperformed their talent level most (as determined by the simple formula WPA-WAR).

Context Winners
Name Team WPA WAR Context Differential
Jayson Werth Nationals 1.50 0.4 1.1
Michael Morse Giants 1.27 0.2 1.07
Denard Span Nationals 1.00 0.1 0.9
Alberto Callaspo Athletics 0.85 0.0 0.85
Khris Davis Brewers 0.55 -0.1 0.65
Aaron Hill Diamondbacks 0.31 -0.3 0.61
Giancarlo Stanton Marlins 1.50 0.9 0.6
Michael Brantley Indians 1.27 0.7 0.57
Chris Colabello Twins 1.06 0.5 0.56
Curtis Granderson Mets 0.15 -0.4 0.55
Gerardo Parra Diamondbacks -0.07 -0.6 0.53
David Murphy Indians 0.97 0.5 0.47
Corey Hart Mariners 0.76 0.3 0.46
Jose Abreu White Sox 1.24 0.8 0.44
James Loney Rays 0.94 0.5 0.44
Victor Martinez Tigers 0.53 0.1 0.43
Ryan Braun Brewers 1.43 1 0.43
Josmil Pinto Twins 0.83 0.4 0.43
Marlon Byrd Phillies 0.52 0.1 0.42
Jason Kubel Twins 0.62 0.2 0.42
Mike Moustakas Royals 0.31 -0.1 0.41
Raul Ibanez Angels -0.02 -0.4 0.38
Neil Walker Pirates 0.62 0.3 0.32
Kyle Seager Mariners 0.42 0.1 0.32
Justin Morneau Rockies 0.90 0.6 0.3
Ruben Tejada Mets -0.10 -0.4 0.3
Billy Butler Royals -0.40 -0.7 0.3
Jason Kipnis Indians 0.77 0.5 0.27
Matt Holliday Cardinals 0.17 -0.1 0.27
Elvis Andrus Rangers 0.66 0.4 0.26

We're left with an interesting group here: good players who have been solid on the season so far (Braun, Stanton, others), okay players who have exceeded their talent (Werth, Callaspo, others) and poor players who haven't been quite as poor as their observed talent would suggest (Ibanez, Parra, others). What about the "context losers"? Have a look:

Context Losers
Name Team WPA WAR Context Differential
Brian Dozier Twins -0.17 1.3 -1.47
Ben Zobrist Rays -0.23 1.1 -1.33
Wil Myers Rays -0.71 0.6 -1.31
Emilio Bonifacio Cubs -0.09 1.1 -1.19
Erick Aybar Angels -0.50 0.6 -1.1
Melky Cabrera Blue Jays 0.09 1.1 -1.01
Jarrod Saltalamacchia Marlins -0.20 0.8 -1
Troy Tulowitzki Rockies 0.82 1.8 -0.98
Jed Lowrie Athletics 0.02 1 -0.98
Alex Rios Rangers -0.17 0.8 -0.97
B.J. Upton Braves -0.66 0.3 -0.96
Everth Cabrera Padres -0.35 0.6 -0.95
Asdrubal Cabrera Indians -0.74 0.2 -0.94
Jonathan Lucroy Brewers -0.03 0.9 -0.93
Jhonny Peralta Cardinals -0.63 0.3 -0.93
Yunel Escobar Rays -0.72 0.2 -0.92
Desmond Jennings Rays -0.11 0.8 -0.91
Brandon Phillips Reds -0.51 0.4 -0.91
Freddie Freeman Braves 0.20 1.1 -0.9
Carlos Gomez Brewers 0.23 1.1 -0.87
Mike Trout Angels 0.83 1.7 -0.87
Andrew McCutchen Pirates 0.45 1.3 -0.85
Rajai Davis Tigers -0.05 0.8 -0.85
Alejandro De Aza White Sox -0.84 0.0 -0.84
Andrelton Simmons Braves -0.21 0.6 -0.81
Matt Adams Cardinals -0.39 0.4 -0.79
Anthony Rendon Nationals -0.09 0.7 -0.79
Marcell Ozuna Marlins -0.09 0.7 -0.79
Charlie Blackmon Rockies 0.93 1.7 -0.77
Alex Gordon Royals -0.16 0.6 -0.76

Here, we're left with another interesting couple of groups: great players who haven't necessarily been great for their teams so far (Trout, McCutchen, others), okay players who haven't been very helpful (Aybar, Adams, others) and some replacement level types who have been downright detrimental (E. Cabrera, De Aza). (I'm personally curious if there's some bias here as it's tough for a player like Trout, who is immensely talented, to have an on-field impact as strong as his talent would indicate. Just like WPA allows a less talented player to shine through context-based outcomes as we saw with Moss, perhaps context will always drag down a player like Trout to some degree. I can't prove that at this point, but it's a thought that might deserve some pondering.)

We've just looked at two different ways to calculate wins, but which is best? Well, that all depends on what you wish to measure. WAR is the more dependable, accurate reflection of talent while WPA is the less predictable record of context-based outcomes. The two are not interchangeable, however, and shouldn't be confused, although they are both useful.

*All stats courtesy of FanGraphs

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Jeff Wiser is an editor and featured writer at Beyond the Box Score and co-author of Inside the 'Zona, an analytical look at the Arizona Diamondbacks. You can follow him on Twitter @OutfieldGrass24.